Scientific Endeavor Research Articles

Broadband polarization-insensitive terahertz absorber based on Ta2O5 snowflake-like structure

Abstract In this paper, an ultra-broadband tantalum pentoxide (Ta2O5) all-dielectric metamaterial absorber is proposed from the far-infrared to the terahertz range, which exhibits polarization-insensitive and wide-angle characteristics. The absorber consistently demonstrates an impressive absorption rate exceeding 90% within the frequency range from 1.1 THz to 20 THz. Such an absorber can have a bandwidth and relative bandwidth ratio of 18.9 THz and 179.15%. We employ an equivalent circuit model to simulate the performance of the absorber using transmission line theory, which facilitates near-perfect absorption by finely tuning the geometrical parameters of the structure to match the input impedance with that of free space. Detailed calculations and analyses of the electric and magnetic field distributions, as well as power loss density, are presented to clarifying the underlying mechanisms of absorption. The design of the proposed absorber inherently provides insensitivity to polarization angles and sustains superior absorption efficiency at substantial incidence angles. An exhaustive exploration of the influence of structural variations on the performance of the absorber has been conducted. Looking ahead, the proposed absorber can be potential application in enhanced terahertz imaging, terahertz communication systems, novel energy harvesting solutions and broad scientific research endeavours.

Employing Evolutionary Computing and Hybrid Artificial Neural Networks to Improve Drug Discovery

An ultimate relevant translational scientific endeavour that contributes to human vulnerability and happiness might be the creation and advancement of medications. Fast drug discovery procedures necessitate using contemporary computational approaches to tackle pharma data's complexities and high complexity. By combining Evolutionary Computing with Hybrid Artificial Neural Networks (EC-HANNs), this research introduces a novel strategy for optimizing and speeding up the drug development process. To handle various drug-target relations, predict the efficacy of compounds, and discover more accurate potential medications, the proposed model employs EC to evolve the computational construction and hyperparameters of HANNs in real-time. This innovation makes the model a flexible framework. Through repeated refinement of EC- HANN designs, the EC Module uses Particle Swarm Optimization (PSO) to choose the best configuration for individual drug discovery tasks. The model's distinctive feature is that it dynamically adjusts the network configuration to match the details of each drug discovery activity by using PSO to optimize the HANN's architecture and hyperparameters. Regarding sequential biological data, the HANN Module employs Convolutional Neural Networks (CNNs) to glean features for pattern recognition over time. By extracting high-level spatial information from genetic data, CNN can better identify prospective medication candidates. When tested on several benchmark datasets, the proposed framework demonstrates superior performance over traditional neural networks across the board regarding prediction accuracy, convergence speed, and model durability. As a powerful tool, this hybrid approach can simplify drug discovery, leading to more efficient drug development.

LUKB: Preparing Local UK Biobank Data for Analysis

Abstract Motivation The UK Biobank data holds immense potential for human health research. However, the complex data preparation and interpretation processes often act as barriers for researchers, diverting them from their core research questions. Results We developed LUKB, an R Shiny-based web tool that simplifies UK Biobank data prepara-tion by automating these pre-processing tasks. LUKB reduces pre-processing time and integrates functions for initial data exploration, allowing researchers to dedicate more time to their scientific en-deavors. Detailed deployment and usage can be found in the supplementary data. Availability and implementation LUKB is freely available at https://github.com/HaiGenBuShang/LUKB.

Performance of chatbots in queries concerning fundamental concepts in photochemistry.

The advent of chatbots raises the possibility of a paradigm shift across society including the most technical of fields with regard to access to information, generation of knowledge, and dissemination of education and training. Photochemistry is a scientific endeavor with roots in chemistry and physics and branches that encompass diverse disciplines ranging from astronomy to zoology. Here, five chatbots have each been challenged with 13 photochemically relevant queries. The chatbots included ChatGPT 3.5, ChatGPT 4.0, Copilot, Gemini Advanced, and Meta AI. The queries encompassed fundamental concepts (e.g., "Why is the fluorescence spectrum typically the mirror image of the absorption spectrum?"), practical matters (e.g., "What is the inner filter effect and how to avoid it?"), philosophical matters ("Please create the most important photochemistry questions."), and specific molecular features (e.g., "Why are azo dyes non-fluorescent?"). The chatbots were moderately effective in answering queries concerning fundamental concepts in photochemistry but were glaringly deficient in specialized queries for dyes and fluorophores. In some instances, a correct response was embedded in verbose scientific nonsense whereas in others the entire response, while grammatically correct, was utterly meaningless. The unreliable accuracy makes present chatbots poorly suited for unaided educational purposes and highlights the importance of domain experts.

Beamtimes and knowledge production times: how big-science research infrastructures shape nations’ domestic and international science production

Frontier scientific discoveries increasingly rely on big-science research infrastructures, such as supercolliders, synchrotron light sources, and space telescopes, whose construction and operation involve intensive international collaboration. This collaborative nature, however, presents a challenge in balancing national interests with the common good, particularly given the substantial fiscal investments involved. This study investigates the effects of one of China’s prominent big-science infrastructures, the Shanghai Synchrotron Radiation Facility (SSRF), on the country’s production of science, differentiating between national and international scientific endeavors. Employing a rigorous difference-in-differences (DID) methodology, it evaluates SSRF’s effects on discipline-level production of publications by domestic researchers and those involving international collaboration. The empirical findings reveal compelling evidence that SSRF has significantly enhanced the production of high-impact national and international publications for disciplines reliant on the facility for experiments, particularly increasing the percentage of high-impact national publications. The findings also underscore the dual role of big-science infrastructures in fostering international research collaboration while simultaneously enhancing nations’ domestic scientific development and competitiveness. Additionally, the study provides valuable insights for research assessment and science policy discussions.

Intelligent Predictive Networks for Cattaneo-Christov Heat and Mass Transfer Dissipated Williamson Fluid Through Double Stratification

This study aims to develop an efficient predictive model for Cattaneo-Christov heat and mass transformation of dissipative Williamson fluid with the effects of double stratification (CCHMT-DWF-DS) using the Levenberg-Marquardt Backpropagation (LMA-BP) algorithm. The under-consideration Williamson fluid flow is magneto-hydro-dynamic, incompressible and two-dimensional through a stretching sheet. The mathematical model of nonlinear partial differential equations for physical phenomena is transformed into ordinary differential equations by means of renowned similarity transformations. The solutions of physical problem are computed by bvp4c technique through MATLAB. The LMA-BP is employed to train a backward neural network capable of accurately predicting velocity, temperature, and concentration profiles under various physical conditions such as changes in the Hartmann number , Prandtl number , Schmidt number , Williamson parameter , the relaxation time of temperature , the relaxation time of concentration , temperature stratification , and concentration stratification for generating a variety of graphical outcomes and statistics. This research is significant for its innovative use of the LMA-BP in analyzing the complex dynamics of non-Newtonian fluids specifically the Williamson fluid, alongside the Cattaneo-Christov heat and mass flux model. The obtaining graphs have been discussed in detail. The thermal and solutal relaxation factors reduce heat and mass flow while fluid motion is delayed by the time-dependent parameter and further reduced by the Hartman number. The Cattaneo-Christov heat flux model enhances simulation accuracy by integrating temporal delays in heat transfer, proving beneficial for sophisticated industrial and scientific endeavors related to non-Newtonian fluids. This analysis offers a powerful predictive tool for applications in thermal management, industrial cooling systems, and biomedical fluid dynamics, advancing machine learning in fluid mechanics.

Early Days in the Hunt Laboratory at UVA, 1969-1980

Arriving at the University of Virginia in the autumn of 1969, Donald Hunt began his 50+ year career in academics with the study of organometallic chemistry, on which he had done his PhD thesis, and mass spectrometry, to which he was introduced while a postdoc in Klaus Biemann’s laboratory at the Massachusetts Institute of Technology. In the 1970s, Hunt’s lab pioneered the use of negative chemical ionization (CI) to enhance sensitivity for studying organic molecules, developed a system for simultaneously obtaining positive and negative CI spectra to augment structure elucidation, and built a prototype triple quadrupole instrument so effective at collisional dissociation that its commercial counterpart became the analytical instrument of choice for mixture analysis for the next decade and beyond. Foreseeing that the future lay in the analysis of biological molecules, by the end of the decade Hunt shifted his focus to peptides. The analysis of protein fragments had suddenly become more accessible thanks to the advent of the triple quadrupole and Barber’s invention of fast atom bombardment. As the ‘80s began and Hunt and his team sought to pursue larger and larger pieces of proteins, his attention turned to the development of mass spectrometers with greater mass range. While recounting their memories of these events, several of Hunt’s students and colleagues pay tribute to his support for them as individuals, as well as to his infectious enthusiasm for scientific endeavors that he so generously shared.

Transition Edge Sensors: Physics and Applications

Transition Edge Sensors (TESs) are amongst the most sensitive cryogenic detectors and can be easily optimized for the detection of massive particles or photons ranging from X-rays all the way down to millimetre radiation. Furthermore, TESs exhibit unmatched energy resolution while being easily frequency domain multiplexed in arrays of several hundred pixels. Such great performance, along with rather simple and sturdy readout and amplification chains make TESs extremely compelling for applications in many fields of scientific endeavour. While the first part of this article is an in-depth discussion on the working principles of Transition Edge Sensors, the remainder of this review article focuses on the applications of Transition Edge Sensors in advanced scientific instrumentation serving as an accessible and thorough list of possible starting points for more comprehensive literature research.

Technical Overview of ISRO and NASA’s First Joint Mission: NASA-ISRO Synthetic Aperture Radar (NISAR) Satellite

The NASA-ISRO Synthetic Aperture Radar (NISAR) mission represents a groundbreaking collaboration aimed at comprehensively monitoring Earth's surface dynamics. Through the fusion of L-band and S-band radar frequencies, NISAR promises unprecedented precision in detecting subtle surface changes, ranging from ecosystem disruptions to ice sheet collapses and natural hazard occurrences. This paper explores the mission's objectives, technology, and significance in advancing our understanding of climate change impacts and hazard mitigation. The partnership between NASA and ISRO, culminating in the signing of agreements in 2014, underscores the international cooperation vital for addressing complex global challenges. With its targeted launch, NISAR heralds a new era in Earth observation, enabled by the fusion of cutting-edge technology and collaborative scientific endeavour.

Diversified subsistence patterns and their influencing factors revealed by ancestral paleodiet during the first millenium BC in Northwest Yunnan, China

The in-depth research into how prehistoric human subsistence patterns responded to environmental shifts during the transcontinental spread of crops, livestock, and cultural interactions between the second and first millenium BC is a pivotal scientific endeavor that has aroused widespread attention. Northwest Yunnan, as a vital corridor for human migration, facilitated ancient human dispersals and fostered cultural exchanges. Analyzing prehistoric subsistence patterns in Yunnan, particularly in Northwest Yunnan, is crucial for understanding the dynamics and repercussions of agricultural expansion in Eurasia during prehistory. This study examined stable isotopes extracted from human bone and plant microfossils extracted from dental calculus samples collected from two sites in Northwest Yunnan. The comprehensive analysis revealed that the inhabitants of Northwest Yunnan during the first millenium BC primarily consumed C3 plants (including rice, wheat, barley, buckwheat, legumes, roots and tubers, etcetera), with C4 plants as supplements (such as millets), alongside a high intake of animal protein. With the integration of existing archaeobotanical and zooarchaeological data from neighboring sites, what emerges is a composite subsistence strategy developed by the ancestors in Northwest Yunnan during the first millenium BC, characterized by coexisting practices of planting-gathering and animal husbandry-fishing/hunting. These diversified subsistence patterns were shaped by the cultural influences from Northwest China and the local natural environment, indicating an adaptation to geographical constraints and a strategic response to climatic fluctuations during periods of low productivity.

The CAT’s race: Who will claim this nobel prize?

This article explores the competitive scientific endeavor to detect the Cosmic FM Background (CFMB), a predicted radiation whose discovery could substantiate the Small Bang model and potentially challenge the prevailing Big Bang paradigm in cosmology. We delve into the theoretical foundation of CFMB, detailing methodologies for its detection and discussing the profound implications such a discovery would hold for astrophysics. The detection of CFMB would not only shift current cosmological theories but also pave the way for new understanding of the universe’s earliest moments.

The global research landscape and future trends in healthcare Total Quality Management

Total Quality Management (TQM) is instrumental in augmenting the quality and efficacy of healthcare service delivery, but a comprehensive evaluation of present and evolving TQM research trends within healthcare research articles is notably absent. This study provides an insightful view into the prevailing international scenarios and upcoming research frontiers in healthcare TQM research field, utilizing bibliometric mapping through VOSviewer. Drawing data from 360 publications in the Web of Science core citation database, it delineates a steady growth in the field over the last 30 years. Research outputs span 51 countries and regions, with notable contributions from the United States, United Kingdom, Netherlands, and Italy. The top five research institutions and numerous authors predominantly hail from the United States. Key keywords in near years encompass healthcare safety, healthcare quality assurance, quality indicators, and the application of Six Sigma management principles. This exploration serves as a pivotal reference for understanding the global research landscape and future trends in healthcare TQM, particularly in guaranteeing quality and safety. Future scientific endeavors will build upon these focus areas, exploring and connecting research gaps in more specialized fields.

Predicting and assessing the impacts of COVID-19 disruption on marine science and sectors in Australia

AbstractBy March 2020 coronavirus disease 2019 (COVID-19) was anticipated to present a major challenge to the work undertaken by scientists. This pandemic could be considered just one of the shocks that human society has had and will be likely to confront again in the future. As strategic thinking about the future can assist performance and planning of scientific research in the face of change, the pandemic presented an opportunity to evaluate the performance of marine researchers in prediction of future outcomes. In March 2020, two groups of researchers predicted outcomes for the Australian marine research sector, and then evaluated these predictions after 18 months. The self-assessed coping ability of a group experienced in ‘futures studies’ was not higher than the less-experienced group, suggesting that scientists in general may be well placed to cope with shocks. A range of changes to scientific endeavours (e.g., travel, fieldwork) and to marine sectors (e.g., fisheries, biodiversity) were predicted over the first 12–18 months of COVID-19 disruption. The predicted direction of change was generally correct (56%) or neutral (25%) for predictions related to the scientific endeavour, and correct (73%) or mixed (9%) for predictions related to sectors that are the focus of marine research. The success of this foresighting experiment suggests that the collective wisdom of scientists can be used by their organisations to consider the impact of shocks and disruptions and to better prepare for and cope with shocks. Graphical abstract Word cloud analysis of free text responses to questions about expected impact of COVID-19 on the activities associated with marine science

On the type specimens of Fragilaria siamensis Østrup, its transfer to Fragilariforma and comments on the biogeography of the genus

Biogeography is a valid scientific endeavour for exploring diatom distributions because the concept of endemism is generally accepted and not considered an irrelevant idea – endemism is taken seriously because it has been documented for many species in many areas around the globe. But to study biogeography meaningfully one does not just need the recognition of endemism. What is required is a problem, such as explaining the diversity of species or species groups in the Southern hemisphere. This requires the identification of species or species groups that are demonstrated to be endemic in at least some of the areas of interest and are related in a very specific way (monophyly). This paper deals with the genus Fragilariforma, which has ca. 30 + included species (taxa) that can be divided into a Northern component and a Southern component, the latter potentially speaking to the origin of the southern hemisphere biota.

Consciousness Under the Spotlight: The Problem of Measuring Subjective Experience.

The study of consciousness is considered by many one of the most difficult contemporary scientific endeavors and confronts several methodological and theoretical challenges. A central issue that makes the study of consciousness so challenging is that, while the rest of science is concerned with problems that can be verified from a "third person" view (i.e., objectively), the study of consciousness deals with the phenomenon of subjective experience, only accessible from a "first person" view. In the present article, we review early (starting during the late 19th century) and later efforts on measuring consciousness and its absence, focusing on the two main approaches used by researchers within the field: objective (i.e., performance based) and subjective (i.e., report based) measures of awareness. In addition, we compare the advantages and disadvantages of both types of awareness measures, evaluate them according to different methodological considerations, and discuss, among other issues, the possibility of comparing them by transforming them to a common sensitivity measure (d'). Finally, we explore several new approaches-such as Bayesian models to support the absence of awareness or new machine-learning based decoding models-as well as future challenges-such as measuring the qualia, the qualitative contents of awareness-in consciousness research.

D’Arcy Thompson and Synthetic Biology—Then and Now

AbstractThough often presented as a recent scientific endeavor, synthetic biology began in the 19th century and was a particularly active field in the years preceding the publication of D’Arcy Thompson’s On Growth and Form. Much synthetic biology of the era was devoted to the construction of nonliving chemical systems that would undergo morphogenesis or dynamic behaviors which had been observed in living organisms. The point was to show that “life-like” structure and behavior could be generated by physicochemical laws and required no vitalist element. D’Arcy Thompson’s careful analysis of physicochemical morphogenetic mechanisms as possible explanations of organic form links closely to this way of thinking. In the modern era, when we can genetically engineer cells to undergo specific behaviors, and program cells to undergo simple morphogenetic behaviors of the kind that Thompson and others felt might underly natural morphogenesis, it is possible to test whether they will in fact produce a predictable multicellular shape. This addresses essentially the same questions about the morphogenetic role of physicochemical forces, such as surface tension, but does so “the other way round”: physicochemical mechanisms are not being used as models for morphogenesis by natural cells but rather as a means to engineer cells to make designed forms.

Leveraging extensive soil, vegetation, fire, and land treatment data to inform restoration across the sagebrush biome

ContextWidespread ecological degradation has prompted calls for massive global investments in ecological restoration, yet limited resources necessitate efficient application of restoration efforts. In western North America, altered fire regimes are increasing the scale of restoration needed to preserve the sagebrush (Artemisia species) biome but prioritizing and implementing effective restoration is complicated by the vast and heterogeneous sagebrush landscape, which includes gradients in climate, disturbance, and species composition.ObjectivesTo develop spatially explicit and context-dependent estimates of treatment efficacy and sagebrush recovery rates.MethodsWe leveraged a suite of spatio-temporally extensive datasets to evaluate the influence of restoration treatments and environmental conditions on trends in post-disturbance sagebrush cover, with an emphasis on understanding differences between sites recovering naturally and sites receiving restoration treatments. We used estimates from these models to develop spatially explicit projections for sagebrush recovery, conditional on disturbance, restoration practice, and environmental conditions.ResultsWe found seeding Artemisia spp. increased sagebrush cover over time relative to natural recovery, but this relationship depended on spring soil moisture availability and treatment methods. Natural recovery was positively influenced by soil moisture and sagebrush cover and negatively influenced by cumulative burns and annual herbaceous cover, while the influence of perennial herbaceous cover varied with soil moisture.ConclusionsOur results provide biome-wide insights and spatially explicit tools that can inform economic cost-effectiveness analyses, restoration prioritization tools, and other scientific endeavors to ensure managers have the tools and information needed to effectively steward the sagebrush biome in a rapidly changing world.

Religion, secularism, and postsecularism in Chinese internet literature

Abstract Internet literature emerged in China in the 1990s and became commercialized in the early 2000s, with readers paying an access fee, which is split between literary platforms and their contracted writers, to access popular novels. While the most popular genre is fantasy, a type of imaginative literature devoted to invoking magic beyond the limits of empirical reality and scientific rationality, the primary source of magic for Chinese fantasy is traditional Chinese cosmology and its concrete applications in everyday practices. These ideas and practices, the onto-epistemic-practical foundation of Chinese religion before the twentieth century, were considered superstitious and targeted for elimination in modernizing and secularization processes. However, they have not only survived but taken up a new life in fantasy novels, which depict them as the antecedents of, alternatives to, or more advanced forms than modern scientific endeavors at engineering natural environments and enhancing human bodies. This is why I see online fantasy literature as a palimpsest bearing the traces of Chinese religion, Chinese secularism, and the social conditions of contemporary China. In bearing such traces, this literature exemplifies the postsecular.

Emphasizing “Integrationism” in Twenty-First Century Science: Another Useful Tool to Generate Better Scientific Paradigms Better Quality Science

The core objective of this paper is to emphasize the importance of “integrationism” as a core and a central method, and as a core philosophy of science, social sciences included, and one that can naturally and reliably be used to generate much better paradigms, better frameworks, and better concepts in science, and higher quality and higher order science as well. We also believe and propose that this technique become vital to scientific endeavour as a whole. In order to better perform the task of laying down the bare essentials of this paper, we review our earlier papers on scientific method of which there have indeed been many published over the last couple of years or so, including our much more recent paper on foundationalism. We also then go on to explain and elucidate why inductivism, including methodological inductivism and nomothetic approaches provide the epistemological basis for this paper, and stand us in very good stead. We also examine and explore other essential prerequisites of this approach including the need and necessity of dogma and ideology-free science, coherentism, reliabilism, internal and external validity, accuracy, rigour, precision, and also explain how this approach can be used to integrate and synthesize paradigms, frameworks, methods, and methodologies as well across a broad spectrum.

Sustainable bioinspired materials for regenerative medicine: balancing toxicology, environmental impact, and ethical considerations

The pursuit of sustainable bioinspired materials for regenerative medicine demands a nuanced balance between scientific advancement, ethical considerations, and environmental consciousness. This abstract encapsulates a comprehensive perspective paper exploring the intricate dynamics of toxicology, environmental impact, and ethical concerns within the realm of bioinspired materials. As the landscape of regenerative medicine evolves, ensuring the biocompatibility and safety of these materials emerges as a pivotal challenge. Our paper delves into the multidimensional aspects of toxicity assessment, encompassing cytotoxicity, genotoxicity, and immunotoxicity analyses. Additionally, we shed light on the complexities of evaluating the environmental impact of bioinspired materials, discussing methodologies such as life cycle assessment, biodegradability testing, and sustainable design approaches. Amid these scientific endeavors, we emphasize the paramount importance of ethical considerations in bioinspired material development, navigating the intricate web of international regulations and ethical frameworks guiding medical materials. Furthermore, our abstract underscores the envisioned future directions and challenges in toxicology techniques, computational modeling, and holistic evaluation, aiming for a comprehensive understanding of the synergistic interplay between sustainable bioinspired materials, toxicity assessment, environmental stewardship, and ethical deliberation.